bcitoolbox


Namebcitoolbox JSON
Version 0.1.0.6 PyPI version JSON
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home_pageNone
SummaryA zero-programming package for Bayesian causal inference model
upload_time2025-07-14 21:41:18
maintainerNone
docs_urlNone
authorevans.zhu
requires_pythonNone
licenseNone
keywords
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requirements No requirements were recorded.
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            BCI Toolbox is a Python implementation of the hierarchical Bayesian Causal Inference (BCI) model for multisensory research. BCI model is a statistical framework for understanding the causal relationships between sensory inputs and prior expectations of a common cause, which can account for human perception in a number of tasks, including temporal numerosity judgment (Shams et al., 2005; Wozny et al., 2008), spatial localization judgment (Körding et al., 2007; Wozny & Shams, 2011), size-weight illusion paradigm (Peters et al., 2016), rubber-hand illusion paradigm (Chancel et al., 2022; Chancel & Ehrsson, 2023).

            

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